In order to save bandwidth for transmitting and storing voice and audio signals, voice and audio coding technologies are applied widely, for example, lossy coding and lossless coding. In the lossy coding, the reconstructed signals are not completely the same as the original signals, but redundant information of signals may be minimized according to the sound source features and the human perception features. In the lossless coding, the reconstructed signals need to be completely the same as the original signals so that the final decoding quality is not impaired at all. Generally, in the lossy coding, the compression ratio is high, but the quality of the reconstructed voice may not be ensured; in the lossless coding, the voice quality is ensured, but the compression ratio is as low as about 50%.
In both the lossy coding and the lossless coding, an LPC (Linear Prediction Coding) model is widely applied to voice coding. In the lossy coding, a typical application of the LPC model is Code Excited Linear Prediction (CELP) coding model. The fundamentals of the CELP coding model are: remove the near sample point redundancy of voice signals by using short-time linear prediction, remove the far sample point redundancy of voice signals by using a long-time predictor, and perform coded transmission for parameters generated in the prediction process and residual signals obtained through the two levels of prediction.
Currently, the LPC analysis of lossy and lossless audio coding/decoding generally involves three modules: windowing module auto-correlation module, and Levinson algorithm module. Residual signals are obtained through linear prediction, and are coded through entropy coding to implement audio compression.
In the process of LPC, the prior art at least exists the following problems:
A fixed window function is applied in the windowing process, which makes the linear prediction performance not optimal.
Alternatively, the input signals undergo two rounds of LPC analysis; in the first round of LPC analysis, a short window is applied to the signals; in the second round of LPC analysis, a long window is applied to the signals, which increases complexity of the LPC analysis.